by A. Pung | Oct 15, 2026 | AI / ML, Botany
TL;DR: In this project, we systematically measure watermelons using 38 different parameters in an effort to predict watermelon sweetness based on its externally measurable characteristics. Generally speaking, the metrics may be grouped as follows: Color: Coloration on...
by A. Pung | Oct 15, 2026 | AI / ML, Botany
TL;DR: In this project, we systematically measure watermelons using 38 different parameters in an effort to predict watermelon sweetness based on its externally measurable characteristics. Generally speaking, the metrics may be grouped as follows: Color: Coloration on...
by A. Pung | Oct 15, 2026 | AI / ML, Botany
UNDER CONSTRUCTION (10/15/26) TL;DR: In this project, I systematically measure watermelons using 38 different parameters in an effort to predict watermelon sweetness based on its externally measurable characteristics. Generally speaking, the metrics may be grouped as...
by A. Pung | Oct 15, 2026 | AI / ML, Botany
TL;DR: In this project, I systematically measure watermelons using 38 different parameters in an effort to predict watermelon sweetness based on its externally measurable characteristics. Generally speaking, the metrics may be grouped as follows: Basic: Date,...
by A. Pung | Oct 12, 2026 | Botany, Electronics
<Work In Progress> TL;DR: This post details the materials, sensors, and motivation behind the atmospheric measurement board used in the FIELD (Frequency & Intensity Experiments on Leaf Development) project. In total, the board utilizes three sensors, listed...
by A. Pung | Oct 12, 2026 | Botany, Electronics
<Work In Progress> TL;DR: This post details the materials, sensors, and motivation behind the atmospheric measurement board used in the FIELD (Frequency & Intensity Experiments on Leaf Development) project. In total, the board utilizes three sensors. As an...
